
This document provides a comprehensive overview of the HCC coding process, focusing on two main components: quality and care gap identification, and ICD and HCC-based risk coding. The process involves extracting patient records over a number of years to identify care gaps and their eligibility, as well as leveraging AI to identify suspected conditions not yet documented.
Begin by providing an overview of the HCC coding product, which focuses on two main areas: identifying quality and care gaps, and performing ICD and HCC-based risk coding. Initially, extract all patient records from the past one to five years to identify any care gaps the patient is eligible for.

This step reduces the denominator criteria for quality and care gaps, ensuring measurement only applies to care gaps for which the patient is actually eligible. Additionally, determine which care gaps are closed and which remain open.

Customize care gaps by insurance type and provider plan to ensure eligibility for the patient. When a care gap is identified as open, review the recommended actions required to close it.

Create an order to establish the subsequent steps necessary to close the care gap. This may involve creating a lab order in the EHR or scheduling an appointment. Next, transition to ICD and HCC coding by reviewing all confirmed conditions based on existing claims.

Utilize AI to identify suspected conditions that might be present based on clinical criteria found in documents, even if they are not yet medically coded or documented.

For instance, an elevated cholesterol level may indicate mixed hyperlipidemia as a potential suspected ICD condition that has not been documented or claimed.

This process offers suggestions to healthcare providers at the point of care, aiding in better documentation and faster closure of care gaps.
